This research is to develop improved methods of calculating inverse solutions for the electrical activity in the heart. These solutions are obtained using electric potentials and magnetic fields measured at the surface of the body. Accurate inverse solutions would provide detailed information that would be of great value in the diagnosis and treatment of heart disease. Present methods of obtaining inverse solutions are not adequate to provide this information; they are too sensitive to noise and modeling errors that exist under clinical conditions. Modeling errors are caused by differences between the actual source in the heart and some assumed model of it such as a multiple dipole model. Modeling errors are also caused by the differences between the actual torso and some model of it. Three ways of developing improved methods are to be investigated. The first is to identify and eliminate or reduce the factors that cause noise and modeling errors to pro-inaccurate solutions for multiple dipole heart models. The second is to use an assumed model in the form of a multipole expansion. Some previous research has shown that the lowest order terms, i.e., the dipole terms, are accurately obtained when higher order terms are included in the model. The third way is to use magnetic or a combination of electric and magnetic data. Previous research has shown that electric and magnetic data can provide different information about the actual source in the body when certain simple modeling errors are present; the situation when realistic modeling errors are present will be investigated.